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Genome projects are scientific endeavours that ultimately aim to determine the complete genome sequence of an organism (be it an animal, a plant, a fungus, a bacterium, an archaean, a protist or a virus) and to annotate protein-coding genes and other important genome-encoded features.[1] The genome sequence of an organism includes the collective DNA sequences of each chromosome in the organism. For a bacterium containing a single chromosome, a genome project will aim to map the sequence of that chromosome. For the human species, whose genome includes 22 pairs of autosomes and 2 sex chromosomes, a complete genome sequence will involve 46 separate chromosome sequences.

Next Generation Sequencing (NGS) may have more about this subject.

The Human Genome Project was a landmark genome project that is already having a major impact on research across the life sciences, with potential for spurring numerous medical and commercial developments.[2]

Genome assembly

Genome assembly refers to the process of taking a large number of short DNA sequences and putting them back together to create a representation of the original chromosomes from which the DNA originated. In a shotgun sequencing project, all the DNA from a source (usually a single organism, anything from a bacterium to a mammal) is first fractured into millions of small pieces. These pieces are then "read" by automated sequencing machines, which can read up to 1000 nucleotides or bases at a time. (The four bases are adenine, guanine, cytosine, and thymine, represented as AGCT.) A genome assembly algorithm works by taking all the pieces and aligning them to one another, and detecting all places where two of the short sequences, or reads, overlap. These overlapping reads can be merged, and the process continues.

Genome assembly is a very difficult computational problem, made more difficult because many genomes contain large numbers of identical sequences, known as repeats. These repeats can be thousands of nucleotides long, and some occur in thousands of different locations, especially in the large genomes of plants and animals.

The resulting (draft) genome sequence is produced by combining the information sequenced contigs and then employing linking information to create scaffolds. Scaffolds are positioned along the physical map of the chromosomes creating a "golden path".

Assembly software

Main article: Sequence assembly

Originally, most large-scale DNA sequencing centers developed their own software for assembling the sequences that they produced. However, this has changed as the software has grown more complex and as the number of sequencing centers has increased. An example of such assembler Short Oligonucleotide Analysis Package developed by BGI for de novo assembly of human-sized genomes, alignment, SNP detection, resequencing, indel finding, and structural variation analysis.[3][4][5]

Genome annotation

Genome annotation is the process of attaching biological information to sequences.[6] It consists of three main steps:

  1. identifying portions of the genome that do not code for proteins
  2. identifying elements on the genome, a process called gene prediction, and
  3. attaching biological information to these elements.

Automatic annotation tools try to perform all this by computer analysis, as opposed to manual annotation (a.k.a. curation) which involves human expertise. Ideally, these approaches co-exist and complement each other in the same annotation pipeline.

The basic level of annotation is using BLAST for finding similarities, and then annotating genomes based on that.[1] However, nowadays more and more additional information is added to the annotation platform. The additional information allows manual annotators to deconvolute discrepancies between genes that are given the same annotation. Some databases use genome context information, similarity scores, experimental data, and integrations of other resources to provide genome annotations through their Subsystems approach. Other databases (e.g. Ensembl) rely on both curated data sources as well as a range of different software tools in their automated genome annotation pipeline.[7]

Structural annotation consists of the identification of genomic elements.

  • ORFs and their localisation
  • gene structure
  • coding regions
  • location of regulatory motifs

Functional annotation consists of attaching biological information to genomic elements.

  • biochemical function
  • biological function
  • involved regulation and interactions
  • expression

These steps may involve both biological experiments and in silico analysis. Proteogenomics based approaches utilize information from expressed proteins, often derived from mass spectrometry, to improve genomics annotations.[8]

A variety of software tools have been developed to permit scientists to view and share genome annotations.

Genome annotation remains a major challenge for scientists investigating the human genome, now that the genome sequences of more than a thousand human individuals and several model organisms are largely complete.[9][10] Identifying the locations of genes and other genetic control elements is often described as defining the biological "parts list" for the assembly and normal operation of an organism.[1] Scientists are still at an early stage in the process of delineating this parts list and in understanding how all the parts "fit together".[11]

Genome annotation is an active area of investigation and involves a number of different organizations in the life science community which publish the results of their efforts in publicly available biological databases accessible via the web and other electronic means. Here is an alphabetical listing of on-going projects relevant to genome annotation:

At Wikipedia, genome annotation has started to become automated under the auspices of the Gene Wiki portal which operates a bot that harvests gene data from research databases and creates gene stubs on that basis.[12]

When is a genome project finished?

When sequencing a genome, there are usually regions that are difficult to sequence (often regions with highly repetitive DNA). Thus, 'completed' genome sequences are rarely ever complete, and terms such as 'working draft' or 'essentially complete' have been used to more accurately describe the status of such genome projects. Even when every base pair of a genome sequence has been determined, there are still likely to be errors present because DNA sequencing is not a completely accurate process. It could also be argued that a complete genome project should include the sequences of mitochondria and (for plants) chloroplasts as these organelles have their own genomes.

It is often reported that the goal of sequencing a genome is to obtain information about the complete set of genes in that particular genome sequence. The proportion of a genome that encodes for genes may be very small (particularly in eukaryotes such as humans, where coding DNA may only account for a few percent of the entire sequence). However, it is not always possible (or desirable) to only sequence the coding regions separately. Also, as scientists understand more about the role of this noncoding DNA (often referred to as junk DNA), it will become more important to have a complete genome sequence as a background to understanding the genetics and biology of any given organism.

In many ways genome projects do not confine themselves to only determining a DNA sequence of an organism. Such projects may also include gene prediction to find out where the genes are in a genome, and what those genes do. There may also be related projects to sequence ESTs or mRNAs to help find out where the genes actually are.

Historical and technological perspectives

Historically, when sequencing eukaryotic genomes (such as the worm Caenorhabditis elegans) it was common to first map the genome to provide a series of landmarks across the genome. Rather than sequence a chromosome in one go, it would be sequenced piece by piece (with the prior knowledge of approximately where that piece is located on the larger chromosome). Changes in technology and in particular improvements to the processing power of computers, means that genomes can now be 'shotgun sequenced' in one go (there are caveats to this approach though when compared to the traditional approach).

Improvements in DNA sequencing technology has meant that the cost of sequencing a new genome sequence has steadily fallen (in terms of cost per base pair) and newer technology has also meant that genomes can be sequenced far more quickly.

When research agencies decide what new genomes to sequence, the emphasis has been on species which are either high importance as model organism or have a relevance to human health (e.g. pathogenic bacteria or vectors of disease such as mosquitos) or species which have commercial importance (e.g. livestock and crop plants). Secondary emphasis is placed on species whose genomes will help answer important questions in molecular evolution (e.g. the common chimpanzee).

In the future, it is likely that it will become even cheaper and quicker to sequence a genome. This will allow for complete genome sequences to be determined from many different individuals of the same species. For humans, this will allow us to better understand aspects of human genetic diversity.

Example genome projects

Main article: List of sequenced eukaryotic genomes

L1 Dominette 01449, the Hereford who serves as the subject of the Bovine Genome Project

Many organisms have genome projects that have either been completed or will be completed shortly, including:

See also


  1. 1.0 1.1 1.2 Pevsner, Jonathan (2009). Bioinformatics and functional genomics, 2nd ed, Hoboken, N.J: Wiley-Blackwell.
  2. Potential Benefits of Human Genome Project Research. Department of Energy, Human Genome Project Information. URL accessed on 2010-06-18.
  3. Li, Ruiqiang, Hongmei Zhu, Jue Ruan, Wubin Qian, Xiaodong Fang, Zhongbin Shi, Yingrui Li, Shengting Li, Gao Shan, Karsten Kristiansen, Songgang Li, Huanming Yang, Jian Wang, Jun Wang (2010-02). De novo assembly of human genomes with massively parallel short read sequencing. Genome Research 20 (2): 265–272.
  4. 4.0 4.1 Rasmussen, Morten, Yingrui Li, Stinus Lindgreen, Jakob Skou Pedersen, Anders Albrechtsen, Ida Moltke, Mait Metspalu, Ene Metspalu, Toomas Kivisild, Ramneek Gupta, Marcelo Bertalan, Kasper Nielsen, M Thomas P Gilbert, Yong Wang, Maanasa Raghavan, Paula F Campos, Hanne Munkholm Kamp, Andrew S Wilson, Andrew Gledhill, Silvana Tridico, Michael Bunce, Eline D Lorenzen, Jonas Binladen, Xiaosen Guo, Jing Zhao, Xiuqing Zhang, Hao Zhang, Zhuo Li, Minfeng Chen, Ludovic Orlando, Karsten Kristiansen, Mads Bak, Niels Tommerup, Christian Bendixen, Tracey L Pierre, Bjarne Grønnow, Morten Meldgaard, Claus Andreasen, Sardana A Fedorova, Ludmila P Osipova, Thomas F G Higham, Christopher Bronk Ramsey, Thomas V O Hansen, Finn C Nielsen, Michael H Crawford, Søren Brunak, Thomas Sicheritz-Pontén, Richard Villems, Rasmus Nielsen, Anders Krogh, Jun Wang, Eske Willerslev (2010-02-11). Ancient human genome sequence of an extinct Palaeo-Eskimo. Nature 463 (7282): 757–762.
  5. Wang, Jun, Wei Wang, Ruiqiang Li, Yingrui Li, Geng Tian, Laurie Goodman, Wei Fan, Junqing Zhang, Jun Li, Juanbin Zhang, Yiran Guo, Binxiao Feng, Heng Li, Yao Lu, Xiaodong Fang, Huiqing Liang, Zhenglin Du, Dong Li, Yiqing Zhao, Yujie Hu, Zhenzhen Yang, Hancheng Zheng, Ines Hellmann, Michael Inouye, John Pool, Xin Yi, Jing Zhao, Jinjie Duan, Yan Zhou, Junjie Qin, Lijia Ma, Guoqing Li, Zhentao Yang, Guojie Zhang, Bin Yang, Chang Yu, Fang Liang, Wenjie Li, Shaochuan Li, Dawei Li, Peixiang Ni, Jue Ruan, Qibin Li, Hongmei Zhu, Dongyuan Liu, Zhike Lu, Ning Li, Guangwu Guo, Jianguo Zhang, Jia Ye, Lin Fang, Qin Hao, Quan Chen, Yu Liang, Yeyang Su, A. san, Cuo Ping, Shuang Yang, Fang Chen, Li Li, Ke Zhou, Hongkun Zheng, Yuanyuan Ren, Ling Yang, Yang Gao, Guohua Yang, Zhuo Li, Xiaoli Feng, Karsten Kristiansen, Gane Ka-Shu Wong, Rasmus Nielsen, Richard Durbin, Lars Bolund, Xiuqing Zhang, Songgang Li, Huanming Yang, Jian Wang (2008-11-06). The diploid genome sequence of an Asian individual. Nature 456 (7218): 60–65.
  6. Stein, L. (2001). Genome annotation: from sequence to biology. Nature Reviews Genetics 2 (7): 493–503.
  7. Ensembl's genome annotation pipeline online documentation.
  8. Gupta, Nitin, Stephen Tanner, Navdeep Jaitly, Joshua N Adkins, Mary Lipton, Robert Edwards, Margaret Romine, Andrei Osterman, Vineet Bafna, Richard D Smith, Pavel A Pevzner (2007-09). Whole proteome analysis of post-translational modifications: applications of mass-spectrometry for proteogenomic annotation. Genome Research 17 (9): 1362–1377.
  9. DOI:10.1371/journal.pbio.1001046
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  10. DOI:10.1038/nature11632
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  11. DOI:10.1038/nature11247
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  12. Huss, Jon W. (2008). A Gene Wiki for Community Annotation of Gene Function. PLoS Biology 6 (7): e175.
  13. Yates, Diana What makes a cow a cow? Genome sequence sheds light on ruminant evolution. (Press Release) EurekAlert!. URL accessed on 2012-12-22.
  14. PMID 19390049 (PMID 19390049)
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External links

Genomics topics
Genome project | Glycomics | Human Genome Project | Proteomics
Chemogenomics | Structural genomics | Pharmacogenetics | Pharmacogenomics | Toxicogenomics
Bioinformatics | Cheminformatics | Systems biology
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